No, the opposite is true.
If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.
1. the sample should be representative thus carefully selected. 2. the sample should be adequate thus significant enough.
2. Are the proportion of the engineering students who view their job prospects as good statistically different from the general college population (show work) Qustion An opinion poll of 100 college student at prestigious engineering school was accomplished on how they viewed their job prospects. 62% of the students said their prospects were good. The portion of good responses for college students in general was 58%
With random sampling, you are hoping to get a representative sample of a whole, however statistically you could get a sample that is very different from the whole it was selected from. The larger the sample proportion of the whole, the better your sample will be. For example, a sample of 10 out of 100 is not as good as 20 out of 100. The bigger the sample the closer to the actual whole average you will get.
Random error and sample size have an inverse relationship...As sample size INCREASES random error DECREASES. There's a good explanation at the related link.
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Yes,Customer services promotes the customer confidence and increase the retention ratio of the customer at a large rate.
From what I can understand, the difference is a technical one: the average person might equate one with the other.A confidence interval is defined to be an interval where you are x% sure that your true value lies.So if I estimated your weight was... 250 lbs (~113 kg or ~18 stone) but said that my confidence interval was 99% for the range of 50 lbs - 500 lbs, that could be true (but worthless).You can see how problems could arise: the larger the interval (range of values), the higher confidence I can have that the true answer is somewhere in there.But the larger my range of values, the less accurate it is as a whole - as in my earlier example, if I estimated your weight to be between 50 - 500 lbs, it would be technically correct, but useless if we were trying to figure out how many people we were trying to fit on say, the last helicopter out of Saigon.A margin of error, statistically speaking, (MoE) is simply defined (as far as I can tell) as a confidence interval of 95%.Notes:A margin of error shrinks as the sample size grows. A good way of estimating a margin of error is the expression (0.98)/(sqrt(n)), where n is the size of the sample in question.You may note that many polls in the news have a margin of error of 3.1% - this is due to the fact that many polls use 1,000 people for a nice 'round' number.A margin of error is unavoidable and ONLY REFLECTS THE SIZE OF THE SAMPLE.It does not, I repeat, not indicate any mistakes in the way the survey is carried out. A sample of 2,000,000 Adolf Hitlers would have a MoE of only 0.06% but might indicate that the continent of Europe believes in the therapeutic power of racial cleansing.Final note:Different people may use the term 'margin of error' slightly differently. Clarify, clarify, clarify!
During the interval, the actors had a rest before the next act in the play.
There is a spell to ease heartache, for confidence, to banish fear, a springtime spell to draw love, to increase attractiveness and confidence, seed of success spell, to draw good energies to you and many more.
yes
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With a good sample, the sample mean gets closer to the population mean.
The principle of a good speech is having confidence and a good write-up. Confidence helps to speak up and a good write up is always helpful.
The election of 1948 demonstrated that a good poll needed a later sample.
Self-confidence.
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